2 results about "List mode" patented technology

The application particularly relates to a kind of asset performance analysis methods based on self-defined algorithm.The asset performance analysis method based on self-defined algorithm is through interface management algorithm factor, sets the mapping relationship of algorithm factor and collected data, and collects and stores algorithm factor data, presents algorithm factor index data in list mode;Algorithm formula is self-defined and set and legality check;Set early warning rule;If the data of current granularity has completed data collection in this period, then trigger algorithm scheduling;Algorithm calculation is carried out based on algorithm factor data;Automatic trigger early warning analysis, generate early warning message according to early warning rule, notify relevant person in charge.The asset performance analysis method based on self-defined algorithm solves the problem that analysis algorithm basic data cannot be quickly expanded, so that the expansion of basic data can be directly applied to algorithm, which can quickly realize the expansion and adjustment of algorithm, and also provides an effective means for the optimization and fine adjustment of algorithm.

Systems and methods for estimating mean randomness include: acquiring list pattern data describing true and delayed coincidences detected by a positron emission tomography (PET) scanner during a scan of an object; determining, based on the list pattern data, delayed coincidences including said crystals for each crystal of the PET scanner and for each of a plurality of time periods of the scan; for each crystal, determining a single event rate associated with each time period based on the delayed coincidences determined for the crystal within the time period; for each time period, determining an estimated mean randomness for each of a plurality of crystal pairs based on the single event rate associated with the time period for each crystal of the crystal pair; and reconstructing an image of the object based on the estimated mean randomness for each time period and the detected true coincidences.